Flowise/packages/components/nodes/llms/Azure OpenAI/AzureOpenAI.ts

199 lines
6.9 KiB
TypeScript

import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { AzureOpenAIInput, OpenAI, OpenAIInput } from 'langchain/llms/openai'
import { BaseCache } from 'langchain/schema'
import { BaseLLMParams } from 'langchain/llms/base'
class AzureOpenAI_LLMs implements INode {
label: string
name: string
version: number
type: string
icon: string
category: string
description: string
baseClasses: string[]
credential: INodeParams
inputs: INodeParams[]
constructor() {
this.label = 'Azure OpenAI'
this.name = 'azureOpenAI'
this.version = 2.0
this.type = 'AzureOpenAI'
this.icon = 'Azure.svg'
this.category = 'LLMs'
this.description = 'Wrapper around Azure OpenAI large language models'
this.baseClasses = [this.type, ...getBaseClasses(OpenAI)]
this.credential = {
label: 'Connect Credential',
name: 'credential',
type: 'credential',
credentialNames: ['azureOpenAIApi']
}
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'Model Name',
name: 'modelName',
type: 'options',
options: [
{
label: 'text-davinci-003',
name: 'text-davinci-003'
},
{
label: 'ada',
name: 'ada'
},
{
label: 'text-ada-001',
name: 'text-ada-001'
},
{
label: 'babbage',
name: 'babbage'
},
{
label: 'text-babbage-001',
name: 'text-babbage-001'
},
{
label: 'curie',
name: 'curie'
},
{
label: 'text-curie-001',
name: 'text-curie-001'
},
{
label: 'davinci',
name: 'davinci'
},
{
label: 'text-davinci-001',
name: 'text-davinci-001'
},
{
label: 'text-davinci-002',
name: 'text-davinci-002'
},
{
label: 'text-davinci-fine-tune-002',
name: 'text-davinci-fine-tune-002'
},
{
label: 'gpt-35-turbo',
name: 'gpt-35-turbo'
}
],
default: 'text-davinci-003',
optional: true
},
{
label: 'Temperature',
name: 'temperature',
type: 'number',
step: 0.1,
default: 0.9,
optional: true
},
{
label: 'Max Tokens',
name: 'maxTokens',
type: 'number',
step: 1,
optional: true,
additionalParams: true
},
{
label: 'Top Probability',
name: 'topP',
type: 'number',
step: 0.1,
optional: true,
additionalParams: true
},
{
label: 'Best Of',
name: 'bestOf',
type: 'number',
step: 1,
optional: true,
additionalParams: true
},
{
label: 'Frequency Penalty',
name: 'frequencyPenalty',
type: 'number',
step: 0.1,
optional: true,
additionalParams: true
},
{
label: 'Presence Penalty',
name: 'presencePenalty',
type: 'number',
step: 0.1,
optional: true,
additionalParams: true
},
{
label: 'Timeout',
name: 'timeout',
type: 'number',
step: 1,
optional: true,
additionalParams: true
}
]
}
async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
const temperature = nodeData.inputs?.temperature as string
const modelName = nodeData.inputs?.modelName as string
const maxTokens = nodeData.inputs?.maxTokens as string
const topP = nodeData.inputs?.topP as string
const frequencyPenalty = nodeData.inputs?.frequencyPenalty as string
const presencePenalty = nodeData.inputs?.presencePenalty as string
const timeout = nodeData.inputs?.timeout as string
const bestOf = nodeData.inputs?.bestOf as string
const streaming = nodeData.inputs?.streaming as boolean
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const azureOpenAIApiKey = getCredentialParam('azureOpenAIApiKey', credentialData, nodeData)
const azureOpenAIApiInstanceName = getCredentialParam('azureOpenAIApiInstanceName', credentialData, nodeData)
const azureOpenAIApiDeploymentName = getCredentialParam('azureOpenAIApiDeploymentName', credentialData, nodeData)
const azureOpenAIApiVersion = getCredentialParam('azureOpenAIApiVersion', credentialData, nodeData)
const cache = nodeData.inputs?.cache as BaseCache
const obj: Partial<AzureOpenAIInput> & BaseLLMParams & Partial<OpenAIInput> = {
temperature: parseFloat(temperature),
modelName,
azureOpenAIApiKey,
azureOpenAIApiInstanceName,
azureOpenAIApiDeploymentName,
azureOpenAIApiVersion,
streaming: streaming ?? true
}
if (maxTokens) obj.maxTokens = parseInt(maxTokens, 10)
if (topP) obj.topP = parseFloat(topP)
if (frequencyPenalty) obj.frequencyPenalty = parseFloat(frequencyPenalty)
if (presencePenalty) obj.presencePenalty = parseFloat(presencePenalty)
if (timeout) obj.timeout = parseInt(timeout, 10)
if (bestOf) obj.bestOf = parseInt(bestOf, 10)
if (cache) obj.cache = cache
const model = new OpenAI(obj)
return model
}
}
module.exports = { nodeClass: AzureOpenAI_LLMs }